how can you override global resource definitions on a job?

To override global resource definitions on a job, you can specify the

resource_defs

parameter when defining the job. This allows you to provide custom resource definitions for that specific job, which will take precedence over the global resources defined in the

Definitions

object. Here's an example from the documentation that illustrates how to override a global resource definition for a specific job:

python from dagster import job, Definitions, ConfigurableResource  class MyResource(ConfigurableResource):     # Resource definition with some configuration     ...  # Define a global resource that will be used by default global_resource = MyResource(...)  # Define a job without specifying resource_defs, it will use the global resource @job def my_job_without_override():     ...  # Define a job with an overridden resource definition @job(resource_defs={"my_resource": MyResource(...)}) def my_job_with_override():     ...  # Create a Definitions object with the global resource defs = Definitions(     jobs=[my_job_without_override, my_job_with_override],     resources={"my_resource": global_resource}, )

In this example,

my_job_without_override

will use the global

MyResource

instance defined in

defs

. However,

my_job_with_override

specifies its own

resource_defs

and will use the overridden

MyResource

instance provided there. Keep in mind that if you provide a subset of the resources in

resource_defs

for a job, the job will only have access to the provided resources, and the resource dictionary is not merged with the global resources. This means that you need to ensure that all required resources for the job are provided when overriding.

@Scout How can I use a mix of global resources and job-level resources when defining a job?

As of the current state of the documentation, when you define a job and specify

resource_defs

, it will replace the global resources provided to

Definitions

with the resources specified in the

resource_defs

. This means that if you want to use a mix of global resources and job-level resources, you need to explicitly include all necessary resources in the

resource_defs

when defining the job. Here's an example based on the documentation:

python from dagster import job, op, ConfigurableResource, Definitions  class MyResource(ConfigurableResource):     # Resource definition with some configuration     ...  class MySecondResource(ConfigurableResource):     # Another resource definition     ...  # Define global resources global_resources = {     "my_resource": MyResource(...),     "my_second_resource": MySecondResource(...), }  # Define a job that uses a mix of global and job-level resources @job(resource_defs={     "my_resource": MyResource(...),  # This overrides the global resource     "my_second_resource": global_resources["my_second_resource"]  # This uses the global resource }) def my_mixed_resources_job():     ...  # Create a Definitions object with the global resources defs = Definitions(     jobs=[my_mixed_resources_job],     resources=global_resources, )

In this example,

my_mixed_resources_job

explicitly defines

my_resource

in its

resource_defs

, which overrides the global definition. It also includes

my_second_resource

from the global resources to ensure it is available to the job. It's important to note that the behavior of merging resources is not supported; you must explicitly define all resources needed by the job in the

resource_defs

if you are providing any job-level resources. If you only want to use global resources, you can omit the

resource_defs

parameter in the job definition, and the job will inherit the resources from the global

Definitions

.

@Scout How would you override resource on an asset job?

To override a resource on an asset job, you can use the

resource_defs

argument when defining the job with

define_asset_job

. This allows you to specify custom resource definitions for the job that will be used when materializing the assets associated with that job. Here's an example of how you might override a resource for an asset job:

python from dagster import define_asset_job, asset, ResourceDefinition  # Define a custom resource class MyCustomResource:     def __init__(self, config):         self.config = config  # Define an asset @asset def my_asset():     # Asset computation logic     ...  # Define an asset job with an overridden resource my_asset_job = define_asset_job(     name="my_asset_job",     selection=[my_asset],     resource_defs={         "my_custom_resource": ResourceDefinition.hardcoded_resource(MyCustomResource(config={"key": "value"}))     } )

In this example,

my_asset_job

is defined with a custom resource called

my_custom_resource

. The

ResourceDefinition.hardcoded_resource

method is used to create a resource definition with hardcoded configuration. When

my_asset_job

is executed, it will use the overridden

my_custom_resource

instead of any global resource definitions with the same key. Remember that when you override resources in this way, you need to ensure that all required resources for the job are provided. If there are other resources that the assets depend on, you must include them in the

resource_defs

as well.

@Scout there is no resource_defs argument in define_asset_job

You are correct; my previous response was inaccurate. The

define_asset_job

function does not have a

resource_defs

argument. In Dagster, resources are supplied to assets, not directly to the job when using

define_asset_job

. Instead, you bind resources to assets, and those resources are then used when the asset job is executed. Here's how you can bind resources to assets:

python from dagster import asset, ResourceDefinition, define_asset_job, with_resources  # Define a custom resource class MyCustomResource:     def __init__(self, config):         self.config = config  # Define an asset @asset(required_resource_keys={"my_custom_resource"}) def my_asset(context):     # You can access the custom resource via context.resources     my_resource = context.resources.my_custom_resource     # Asset computation logic     ...  # Create a resource definition for your custom resource my_custom_resource_def = ResourceDefinition.hardcoded_resource(MyCustomResource(config={"key": "value"}))  # Bind the resource to the asset my_asset_with_resource = with_resources([my_asset], {"my_custom_resource": my_custom_resource_def})  # Define an asset job my_asset_job = define_asset_job(     name="my_asset_job",     selection=[my_asset_with_resource] )

In this example, the

with_resources

function is used to bind the

my_custom_resource

resource to the

my_asset

asset. When

my_asset_job

is executed, it will use the resources bound to the assets included in the job. If you have a global resource that you want to override for a specific asset within a job, you would redefine the asset with the new resource binding and include that redefined asset in the job selection.